Bürgerwissenschaftliche Forschungsansätze in Medizin und Gesundheitsforschung: ausgewählte Begriffe mit Fokus auf den Beteiligungsgrad

In den Bürgerwissenschaften, auch bekannt unter dem englischen Begriff Citizen Science, existiert eine Vielzahl an Forschungsansätzen und Methoden. Während diese in vielen wissenschaftlichen Disziplinen gut etabliert sind, finden sich augenscheinlich relativ wenige davon in der medizinischen und Gesundheitsforschung. Allerdings zeigt ein Blick in die Praxis, dass bürgerwissenschaftliche Ansätze in der Medizin und Gesundheitsforschung durchaus praktiziert werden, jedoch häufig unter anderen Namen. Der Artikel bietet aus interdisziplinärer Perspektive einen (selektiven) Überblick über Begriffe, reflektiert diese und die dahinterstehenden Methoden und diskutiert sie vergleichend. Im Fokus steht dabei der Grad der Beteiligung der Bürger*innen bzw. Patient*innen an wissenschaftlicher Forschung.In citizen science, a variety of research approaches and methods exist. While these are well established in many scientific disciplines, there are apparently relatively few of them in medical and health research. However, a glance at practice shows that citizen science approaches are indeed practiced in medical and health research, but often under different names. The paper therefore provides a (selective) overview of these terms, reflects on them and the methods behind them, and discusses them comparatively from an interdisciplinary perspective. The focus is on the degree of active participation of citizens and patients in research

Readability of English, German, and Russian Disease-Related Wikipedia Pages: Automated Computational Analysis

BackgroundWikipedia is a popular encyclopedia for health- and disease-related information in which patients seek advice and guidance on the web. Yet, Wikipedia articles can be unsuitable as patient education materials, as investigated in previous studies that analyzed specific diseases or medical topics with a comparatively small sample size. Currently, no data are available on the average readability levels of all disease-related Wikipedia pages for the different localizations of this particular encyclopedia. ObjectiveThis study aimed to analyze disease-related Wikipedia pages written in English, German, and Russian using well-established readability metrics for each language. MethodsWikipedia database snapshots and Wikidata metadata were chosen as resources for data collection. Disease-related articles were retrieved separately for English, German, and Russian starting with the main concept of Human Diseases and Disorders (German: Krankheit; Russian: Заболевания человека). In the case of existence, the corresponding International Classification of Diseases, Tenth Revision (ICD-10), codes were retrieved for each article. Next, the raw texts were extracted and readability metrics were computed. ResultsThe number of articles included in this study for English, German, and Russian Wikipedia was n=6127, n=6024, and n=3314, respectively. Most disease-related articles had a Flesch Reading Ease (FRE) score <50.00, signaling difficult or very difficult educational material (English: 5937/6125, 96.93%; German: 6004/6022, 99.7%; Russian: 2647/3313, 79.9%). In total, 70% (7/10) of the analyzed articles could be assigned an ICD-10 code with certainty (English: 4235/6127, 69.12%; German: 4625/6024, 76.78%; Russian: 2316/3314, 69.89%). For articles with ICD-10 codes, the mean FRE scores were 28.69 (SD 11.00), 20.33 (SD 9.98), and 38.54 (SD 13.51) for English, German, and Russian, respectively. A total of 9 English ICD-10 chapters (11 German and 10 Russian) showed significant differences: chapter F (FRE 23.88, SD 9.95; P<.001), chapter E (FRE 25.14, SD 9.88; P<.001), chapter H (FRE 30.04, SD 10.57; P=.049), chapter I (FRE 30.05, SD 9.07; P=.04), chapter M (FRE 31.17, 11.94; P<.001), chapter T (FRE 32.06, SD 10.51; P=.001), chapter A (FRE 32.63, SD 9.25; P<.001), chapter B (FRE 33.24, SD 9.07; P<.001), and chapter S (FRE 39.02, SD 8.22; P<.001). ConclusionsDisease-related English, German, and Russian Wikipedia articles cannot be recommended as patient education materials because a major fraction is difficult or very difficult to read. The authors of Wikipedia pages should carefully revise existing text materials for readers with a specific interest in a disease or its associated symptoms. Special attention should be given to articles on mental, behavioral, and neurodevelopmental disorders (ICD-10 chapter F) because these articles were most difficult to read in comparison with other ICD-10 chapters. Wikipedia readers should be supported by editors providing a short and easy-to-read summary for each article

Transition probabilities of HER2-positive and HER2-negative breast cancer patients treated with Trastuzumab obtained from a clinical cancer registry dataset

Records of female breast cancer patients were selected from a clinical cancer registry and separated into three cohorts according to HER2-status (human epidermal growth factor receptor 2) and treatment with or without Trastuzumab (a humanized monoclonal antibody). Propensity score matching was used to balance the cohorts. Afterwards, documented information about disease events (recurrence of cancer, metastases, remission of local/regional recurrences, remission of metastases and death) found in the dataset was leveraged to calculate the annual transition probabilities for every cohort

DNVF-Memorandum - Health and Medical Apps

Kramer U, Borges U, Fischer F, Hoffmann W, Pobiruchin M, Vollmar HC. DNVF-Memorandum – Gesundheits- und Medizin-Apps (GuMAs) . GESUNDHEITSWESEN. 2019;81(10):E154-E170.Mit der Nutzung von Gesundheits- und Medizin-Apps sind große Erwartungen an eine Verbesserung der Qualität und Effizienz von Präventions- und Versorgungskonzepten verknüpft. In weiten Bevölkerungsschichten ist die Bereitschaft zur Nutzung groß. Es fehlt jedoch belastbare Evidenz, um ausgehend vom derzeitigen, weitgehend unregulierten Angebot, Bedarf, Qualität und Sicherheit dieser Anwendungen einschätzen zu können. Aus diesem Grund adressiert die AG Digital Health im vorliegenden Memorandum wichtige Fragestellungen wie Angebot, objektiven Bedarf und Nettonutzen von Gesundheits- und Medizin-Apps (GuMAs), ethische Standards, Risiken und GuMAs als Forschungsressource, die von der Versorgungsforschung u. a. durch geeignete methodische Ansätze untersucht und beantwortet werden sollten. Diese Fragestellungen beziehen sich auf die Aspekte Patientensicherheit, Prozess- und Ergebnisqualität, versorgungsrelevante Aspekte digitaler Anwendungen und deren Einsatz in und für die wissenschaftliche Forschung.There are huge expectations to improve quality and efficiency of prevention and healthcare by using digital health applications. In contrast to the dynamically growing supply and a high affinity of large parts of the population to use health and medical apps, there is a lack of data and methods to assess quality, benefit, and patient safety with health apps, most of them are not yet regulated.This memorandum outlines core questions that should be addressed by future health services research in order to evaluate the impact of health and medical apps on quality of processes and patient outcomes and to take advantage of their potential as new data sources for scientific research

Assessment of SARS-CoV-2 Infection among Healthcare Workers of a German COVID-19 Treatment Center

To date, more than 160 million people have been infected with COVID-19 worldwide. In the present study, we investigated the history of SARS-CoV-2 infection among 3067 healthcare workers (HCW) in a German COVID-19 treatment center during the early phase of the pandemic (July 2020) based on the seroprevalence of SARS-CoV-2 antibodies and self-reported previous PCR results. The results demonstrate a low prevalence of SARS-CoV-2 infection (n = 107 [3.5%]) with no increased risk for employees with a high level of patient exposure in general or working in COVID-19-confined areas in particular. This suggests that the local hygiene standards implemented in our hospital during the first wave of COVID-19 pandemic were effective in preventing patient-to-HCW transmission. No evidence for highly mobile staff serving as a vector for SARS-CoV-2 transmission could be found. In addition, impairment of smell and/or taste was strongly associated with SARS-CoV-2 history